Tangible user interfaces : past, present and future directions

In the last two decades, Tangible User Interfaces (TUIs) have emerged as a new interface type that interlinks the digital and physical worlds. Drawing upon users' knowledge and skills of interaction with the real non-digital world, TUIs show a potential to enhance the way in which people interact with and leverage digital information. However, TUI research is still in its infancy and extensive research is required in or- der to fully understand the implications of tangible user interfaces, to develop technologies that further bridge the digital and the physical, and to guide TUI design with empirical knowledge. This paper examines the existing body of work on Tangible User In- terfaces. We start by sketching the history of tangible user interfaces, examining the intellectual origins of this field. We then present TUIs in a broader context, survey application domains, and review frame- works and taxonomies. We also discuss conceptual foundations of TUIs including perspectives from cognitive sciences, phycology, and philoso- phy. Methods and technologies for designing, building, and evaluating TUIs are also addressed. Finally, we discuss the strengths and limita- tions of TUIs and chart directions for future research

ImageJ2: ImageJ for the next generation of scientific image data

ImageJ is an image analysis program extensively used in the biological sciences and beyond. Due to its ease of use, recordable macro language, and extensible plug-in architecture, ImageJ enjoys contributions from non-programmers, amateur programmers, and professional developers alike. Enabling such a diversity of contributors has resulted in a large community that spans the biological and physical sciences. However, a rapidly growing user base, diverging plugin suites, and technical limitations have revealed a clear need for a concerted software engineering effort to support emerging imaging paradigms, to ensure the software's ability to handle the requirements of modern science. Due to these new and emerging challenges in scientific imaging, ImageJ is at a critical development crossroads. We present ImageJ2, a total redesign of ImageJ offering a host of new functionality. It separates concerns, fully decoupling the data model from the user interface. It emphasizes integration with external applications to maximize interoperability. Its robust new plugin framework allows everything from image formats, to scripting languages, to visualization to be extended by the community. The redesigned data model supports arbitrarily large, N-dimensional datasets, which are increasingly common in modern image acquisition. Despite the scope of these changes, backwards compatibility is maintained such that this new functionality can be seamlessly integrated with the classic ImageJ interface, allowing users and developers to migrate to these new methods at their own pace. ImageJ2 provides a framework engineered for flexibility, intended to support these requirements as well as accommodate future needs

Multiplierz: An Extensible API Based Desktop Environment for Proteomics Data Analysis

BACKGROUND. Efficient analysis of results from mass spectrometry-based proteomics experiments requires access to disparate data types, including native mass spectrometry files, output from algorithms that assign peptide sequence to MS/MS spectra, and annotation for proteins and pathways from various database sources. Moreover, proteomics technologies and experimental methods are not yet standardized; hence a high degree of flexibility is necessary for efficient support of high- and low-throughput data analytic tasks. Development of a desktop environment that is sufficiently robust for deployment in data analytic pipelines, and simultaneously supports customization for programmers and non-programmers alike, has proven to be a significant challenge. RESULTS. We describe multiplierz, a flexible and open-source desktop environment for comprehensive proteomics data analysis. We use this framework to expose a prototype version of our recently proposed common API (mzAPI) designed for direct access to proprietary mass spectrometry files. In addition to routine data analytic tasks, multiplierz supports generation of information rich, portable spreadsheet-based reports. Moreover, multiplierz is designed around a "zero infrastructure" philosophy, meaning that it can be deployed by end users with little or no system administration support. Finally, access to multiplierz functionality is provided via high-level Python scripts, resulting in a fully extensible data analytic environment for rapid development of custom algorithms and deployment of high-throughput data pipelines. CONCLUSION. Collectively, mzAPI and multiplierz facilitate a wide range of data analysis tasks, spanning technology development to biological annotation, for mass spectrometry-based proteomics research.Dana-Farber Cancer Institute; National Human Genome Research Institute (P50HG004233); National Science Foundation Integrative Graduate Education and Research Traineeship grant (DGE-0654108

EGO: a personalised multimedia management tool

The problems of Content-Based Image Retrieval (CBIR) sys- tems can be attributed to the semantic gap between the low-level data representation and the high-level concepts the user associates with images, on the one hand, and the time-varying and often vague nature of the underlying information need, on the other. These problems can be addressed by improving the interaction between the user and the system. In this paper, we sketch the development of CBIR interfaces, and introduce our view on how to solve some of the problems of the studied interfaces. To address the semantic gap and long-term multifaceted information needs, we propose a "retrieval in context" system. EGO is a tool for the management of image collections, supporting the user through personalisation and adaptation. We will describe how it learns from the user's personal organisation, allowing it to recommend relevant images to the user. The recommendation algorithm is detailed, which is based on relevance feedback techniques

A fast and robust hand-driven 3D mouse

The development of new interaction paradigms requires a natural interaction. This means that people should be able to interact with technology with the same models used to interact with everyday real life, that is through gestures, expressions, voice. Following this idea, in this paper we propose a non intrusive vision based tracking system able to capture hand motion and simple hand gestures. The proposed device allows to use the hand as a "natural" 3D mouse, where the forefinger tip or the palm centre are used to identify a 3D marker and the hand gesture can be used to simulate the mouse buttons. The approach is based on a monoscopic tracking algorithm which is computationally fast and robust against noise and cluttered backgrounds. Two image streams are processed in parallel exploiting multi-core architectures, and their results are combined to obtain a constrained stereoscopic problem. The system has been implemented and thoroughly tested in an experimental environment where the 3D hand mouse has been used to interact with objects in a virtual reality application. We also provide results about the performances of the tracker, which demonstrate precision and robustness of the proposed syste

1st INCF Workshop on Sustainability of Neuroscience Databases

The goal of the workshop was to discuss issues related to the sustainability of neuroscience databases, identify problems and propose solutions, and formulate recommendations to the INCF. The report summarizes the discussions of invited participants from the neuroinformatics community as well as from other disciplines where sustainability issues have already been approached. The recommendations for the INCF involve rating, ranking, and supporting database sustainability

Image Semantics in the Description and Categorization of Journalistic Photographs

This paper reports a study on the description and categorization of images. The aim of the study was to evaluate existing indexing frameworks in the context of reportage photographs and to find out how the use of this particular image genre influences the results. The effect of different tasks on image description and categorization was also studied. Subjects performed keywording and free description tasks and the elicited terms were classified using the most extensive one of the reviewed frameworks. Differences were found in the terms used in constrained and unconstrained descriptions. Summarizing terms such as abstract concepts, themes, settings and emotions were used more frequently in keywording than in free description. Free descriptions included more terms referring to locations within the images, people and descriptive terms due to the narrative form the subjects used without prompting. The evaluated framework was found to lack some syntactic and semantic classes present in the data and modifications were suggested. According to the results of this study image categorization is based on high-level interpretive concepts, including affective and abstract themes. The results indicate that image genre influences categorization and keywording modifies and truncates natural image description